Extensive vegetation restoration projects have been widely implemented on the Loess Plateau, China, since 1998. In addition, increasing attention has been paid to the influence of revegetation on soil water. However, the response of the soil water content (SWC) to vegetation construction and management has not been adequately studied. In this study, three types of typical artificial vegetation on level bench land were selected, including Pinus tabulaeformis Carr., Prunus sibirica L., and Hippophae rhamnoides Linn., with the natural grassland used as a control group in Wuqi County. The 0–160 cm SWC was monitored biweekly from August 2010 to June 2013 using a portable time domain reflectometry system. The serial autocorrelation test, Mann–Kendall trend test, and prewhitening Mann–Kendall test were employed to systematically analyze the trends in soil water dynamics. The results show that the SWC of the three selected artificial forests/shrub had a significant accumulation process in the 0–160 cm profile during the monitoring period, whereas such an increasing tendency was not observed for natural grassland. Furthermore, the greatest responses were observed in the Pinus tabulaeformis Carr. plantation.

Precipitation data from nine meteorological stations in arid oases of Hexi Corridor, northwest China during 1970–2012 were analyzed to detect trends in precipitation and Standardized Precipitation Index (SPI) at multiple time scales using linear regression, Mann–Kendall and Spearman’s Rho tests. The results found that annual precipitation in the observed stations was rare and fell into the arid region category according to the aridity index analysis. The monthly analysis of precipitation found that three stations showed significant increasing trends in different months, while on the annual level, only Yongchang station had a significant increasing trend. The analysis of SPI-12 found three main drought intervals, i.e., 1984–1987, 1991–1992 and 2008–2011, and an extremely dry year among the stations was recorded in 1986; the southeast and middle portions of the study area are expected to have more precipitation and less dry conditions.

Urban energy consumption is mostly concentrated in industrial regions, and carbon emissions from industrial land use have significantly increased as a result of fast urbanization and industrialization. In the battle against climate change, the affluent regions of developing countries are increasingly being used as models for reducing carbon emissions. Therefore, in order to accomplish global sustainable development, it is crucial to understand how industrial land use and carbon emissions are decoupled in wealthy areas of rising nations. This study investigates the decoupling effects and the factors influencing them in six East Chinese provinces and one city between 2005 and 2020 using the Tapio decoupling model and the LMDI decomposition approach. At the same time, the industrial carbon emissions from 2021 to 2035 were predicted using a BP neural network model combined with scenario analysis. The findings indicate that: (1) From 29.921 million tons in 2005 to 40.2843 million tons in 2020, the carbon emissions from industrial land in the East China area have nearly doubled. Of these, Shandong and Jiangsu emit more than half of the region’s total emissions around East China. (2) The decoupling effect analysis shows the East China region’s decoupling trajectory’s phased characteristics, with the degree of decoupling gradually increasing from weak decoupling (2006–2012) to strong decoupling (2013–2018) and finally to negative decoupling (2019–2020). (3) The primary causes of the rise in carbon emissions in the East China region are the scale of per capita economic output and industrial land use. (4) The overall industrial carbon peak time in East China is roughly distributed between 2028 and 2032. It is expected that Shanghai, Shandong, Jiangsu, and Zhejiang will be among the first to achieve carbon emission peak.

Urban development of clusters situated along rivers significantly affects the health of the river ecosystems, the quality of urban environments, and the overall well-being of local communities. Ecosystem service supply value (ESSV) measures the delivery of ecosystem goods and services within a specific timeframe in a particular area. Using the lower Yellow River urban agglomeration (Shandong section) as a case, we comprehensively applied land use structure and intensity change analysis, quantitative calculation of ESS, and geographical probe methods to unveil ESS and its mechanism of response to the spatio-temporal evolution of the intensity of land use in urban agglomeration along the river. The key results were as follows: (1) Over the past two decades, farmland and construction land areas have continued to decrease and increase, respectively, with the intensity of land use change being highest from 2005 to 2010. (2) ESS has continued to rise over the past 20 years, with the income in 2020 being 11.142 billion yuan, an increase of 31.13%. The “low-value areas” are mainly concentrated in Liaocheng City, Dezhou City, and Tai’an City, which are characterized by predominantly flat terrains where farmland constitutes the principal land use type. Conversely, “high-value areas” are largely in the counties bordering the Yellow River, including the upper estuary in the north and the rugged, southeastern terrains. (3) Areas with concentrated ESSV were primarily localized in the northern estuary area and along the Yellow River in a scattered point-like pattern. The spatial distribution of hotspots has become increasingly concentrated, transitioning from points to planes. Conversely, cold spots initially increased in number before subsequently decreasing. Waterbody was the most sensitive ESSV-determining factor. (4) The spatial heterogeneity of ESSV emerges as a consequence of the interaction of multiple factors, and among these interactions, those involving NDVI and POP contain the greatest explanatory power. Our findings are expected to offer a scientific foundation for optimizing land spatial patterns and enhancing ecological management in the lower Yellow River region.

Carbon emissions (CE) from expanding construction land (CL), a vital territory for human production and habitation, have contributed to climate change worldwide. The Yellow River Basin (YRB), an essential economic region and energy supply base in China, is experiencing rapid urbanization, and the contradiction between economic development and ecological protection is increasingly acute. Consequently, a thorough examination of the spatial and temporal change features of carbon emissions from construction land (CECL) and its decoupling from economic growth (EG) is crucial for the maintaining development of the region. This study adopts the IPCC carbon emission coefficient approach for measuring the CECL in the YRB from 2010 to 2021. The temporal and spatial variation features of CECL in the YRB were revealed using ArcGIS software and the standard deviation ellipse (SDE) model. The decoupling effect between CECL and EG was analyzed using the Tapio decoupling model and innovatively combined with the Logarithmic Mean Divisia Index (LMDI) method to explore the influence of five main drivers on the decoupling effect. This study found that: (1) The CECL rose from 2.463 billion tons in 2010 to 3.329 billion tons in 2021. The spatial layout of CECL is “high in the east and low in the west”. (2) The SDE of CECL is distributed in the direction of “northeast to southwest”, and the gravity center’s moving path is “northwest to northeast to northwest”; (3) weak decoupling (WD) is the main decoupling state between CECL and EG; (4) the economic output effect and the construction land (CL) scale effect are the two main factors inhibiting the decoupling of CECL, while the energy intensity effect, the population density effect, and the energy structure effect are the main elements motivating the decoupling of CECL. This study provides specific references and bases for the YRB in China and other countries and regions with similar levels of development in promoting green and ecologically friendly initiatives and achieving low-carbon utilization of regional land and sustainable development.